Micro Milling

Kuram, Emel; Özçelik, Babür

doi:10.1007/978-3-642-45176-8_12

Cited by 7 publications

(2 citation statements)

References 109 publications

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“…However, micro-milling requires tight machining monitoring due to some specific problems. Rapid tool wear [6], premature tool breakage [7], tool deflection [8], tool run-out [9], and plowing [10] are the primary specific problems in micro-milling, and they have a negligible effect on macro-milling as a counterpart. The presence of tool wear has been identified as a significant factor leading to poor results in micro-milling, namely, in terms of low accuracy and surface integrity [11].…”

Section: Introductionmentioning

confidence: 99%

Tool Wear Monitoring in Micro-Milling Based on Digital Twin Technology with an Extended Kalman Filter

Christiand,

Kiswanto,

Baskoro

et al. 2024

JMMP

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In order to avoid catastrophic events that degrade the quality of machined products, such as tool breakage, it is vital to have a prognostic system for monitoring tool wear during the micro-milling process. Despite the long history of the tool wear monitoring field, creating such a system to track, monitor, and foresee the rapid progression of tool wear still needs to be improved in the application of micro-milling. On the other hand, digital twin technology has recently become widely recognized as significant in manufacturing and, notably, within the Industry 4.0 ecosystem. Digital twin technology is considered a potential breakthrough in developing a prognostic tool wear monitoring system, as it enables the tracking, monitoring, and prediction of the dynamics of a twinned object, e.g., a CNC machine tool. However, few works have explored the digital twin technology for tool wear monitoring, particularly in the micro-milling field. This paper presents a novel tool wear monitoring system for micro-milling machining based on digital twin technology and an extended Kalman filter framework. The proposed system provides wear progression notifications to assist the user in making decisions related to the machining process. In an evaluation using four machining datasets of slot micro-milling, the proposed system achieved a maximum error mean of 0.038 mm from the actual wear value. The proposed system brings a promising opportunity to widen the utilization of digital twin technology with the extended Kalman filter framework for seamless data integration for wear monitoring service.

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Section: Introductionmentioning

confidence: 99%

Tool Wear Monitoring in Micro-Milling Based on Digital Twin Technology with an Extended Kalman Filter

Christiand,

Kiswanto,

Baskoro

et al. 2024

JMMP

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“…Micromilling is widely used in aerospace, modern medicine, architecture, and microelectronics because of its advantages of high processing precision, high processing efficiency, and ability to process three-dimensional precision microparts [1][2][3][4]. Compared with conventional milling, micromilling has more stringent requirements for surface quality.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Three-Dimensional Surface Roughness in Microgroove Based on Bidimensional Empirical Mode Decomposition

Jiang

et al. 2022

Micromachines

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Micromilling is an extremely important advanced manufacturing technology in the micromanufacturing industry. Compared with the traditional milling process, micromilling has stricter requirements on the surface roughness of the workpiece, and the roughness of the microcurved surface is not easy to measure. In order to more accurately characterize the curved surface morphology of the microgrooves obtained by micromilling, this paper proposes a method to extract the reference plane of the curved surface based on the bidimensional empirical mode decomposition algorithm and characterize the three-dimensional surface roughness of the curved surface. First, we synthesize the morphologies of the microgrooves by simulated non-Gaussian rough surfaces and models of textures. Second, the bidimensional empirical mode decomposition algorithm was used to extract the reference planes of the simulated microgrooves. Third, the three-dimensional roughness parameters suitable for the curved surfaces of microgrooves were selected to establish an evaluation system. The results show that the mean squared errors of the reference planes are below 1%, so bidimensional empirical mode decomposition can effectively extract reference planes, and the evaluation system of three-dimensional surface roughness proposed in this paper reflects morphological characteristics of the curved surfaces of microgrooves more thoroughly than that of two-dimensional surface roughness parameters.

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The micro-cutting performance of cermet and coated WC micro-mills in machining of TC4 alloy micro-grooves

Wang

Zou

Huang

et al. 2018

Int J Adv Manuf Technol

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Micro Milling

Cited by 7 publications

References 109 publications

Tool Wear Monitoring in Micro-Milling Based on Digital Twin Technology with an Extended Kalman Filter

Tool Wear Monitoring in Micro-Milling Based on Digital Twin Technology with an Extended Kalman Filter

Evaluation of Three-Dimensional Surface Roughness in Microgroove Based on Bidimensional Empirical Mode Decomposition

The micro-cutting performance of cermet and coated WC micro-mills in machining of TC4 alloy micro-grooves

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